International Journal of Engineering Works- ISSN:2409-2770

International Journal of Engineering works

Kambohwell Publishers Enterprise

www.kwpublisher.com

Vol. 1,PP. 10-14, Sept. 2014

Interference Mitigation in LTE HetNet by Resource Allocation

Fakhar Abbas, Naveed Ur Rehman, Mohammad Irshad Zahoor, Man Jamil

Abstract — To provide high date rate for indoor services and
communication, femtocells and microcells are planned in LTE-
Advance system but main problem is how to reduce the
interference between micro and femto cells and in the middle
of the femtocells. In this paper we proposed regional Average
channel state (RACS) to estimate the influence of interference
and then we proposed hybrid clustering based on interference
graph (HCIG) to reduce interference between femtocells and
microcells. Based on the Results our scheme is given to reduce
the interference and improve the spectrum efficiency.

Keywords — Heterogeneous Network, Hybrid clustering
interference graph, Regional average channel state, Micro
User, Pico User etc.

I. Introduction

Reduction of cell sizes and transmission distances is one of
the most effective methods to improve system capacity and
cellular coverage, through which there has been 1600x gain in
system capacity improvement since 1957 [1].

In categorize to provide high quality for those users at
home and business center the Third Generation Partnership
Project Long Term Evolution (3 GPP LTE) has introduced low
power nodes placed indoors, such as femtocells [2]. In case of
the same bandwidth used by macro and femtocells, interference
in the system is the key problem due to the randomness
deployment of femtocell.

There are three types of frequency assignment schemes in
the femtocell network [3]. The first approach is called shared
frequency allocation (SFA) in this case same spectrum resource
is used in macro and femto cells. This gives us results in high
spectrum efficiency, while the co-channel interference may
gravely humiliate the system performance. Another approach is
called partitioned frequency allocation (PFA): femtocell uses
partial spectrum while macrocell uses the remaining. While
this scheme avoids interference between two tiers spectrum
efficiency decreases critically. The last approach is called
partial shared frequency allocation (PSFA): femtocell uses part
of the bandwidth resources and macrocell uses all the available
spectrum resources. It accomplishes cooperation between

Fakkar Abbas: College of Information and Communication Engineering, Harbin
Engineering University, China, 0086-18845073024, fakkhar.14@gmail.com
Naveed Ur Rehman: College of Information and Communication Engineering,
Habin Engineering University China, 0086-13009848100, p0701 08 @ nu.edu. pk
Mohammad Irshad Zahoor: College of Information and Communication
Engineering, Habin Engineering University , engineerirshad89@gmail.com
Man Jamil: IGSES, Kyushu University, Japan, irfan.edu.cn@gmail.com

interference reduction and spectrum efficiency
enhancement.

Numerous schemes have been proposed to reduce the
interference in the LTE heterogeneous network (HetNet)
mainly by means of resource allocation and power control. The
cell is divided to inner and outer part in [4], and the femto user
(FUE) in inner region uses the sub-band different from the
Macro Base Station (MBS) to avoid interference. A resource
management scheme based on fractional frequency reuse
(FFR) is given in [6], in which orthogonal resources are used
between FBS and MBS. Subject to the constraint on the
minimum target SINR realized in macrocell, an iterative power
selection algorithm is presented in [7] to maximize the system
performance.

Recently graph theory is extensively used on the
diminution of interference in LTE network. The vertex, which
is generally Base Station (BS) in the traditional interference
graph modeling schemes, expands to UE and femtocell BS
(FBS) now. In OFDMA macrocell, Necker [8] introduces
interference graph to resolve the interference coordination
problem and presents graph coloring heuristic scheme to avoid
interference, in which two graph nodes connected by an edge
can't be assigned the same color. [9] Extends the graph vertex
to UEs. However, the overhead of updating the graph is very
high, because the MUE node is moving every time. For macro
and femto heterogeneous system, graph-based adaptive
frequency reuse (AFR) scheme is presented in [10] in which
the FBS is taken as the vertex of graph to avoid interference
among FBSs. However, the interference between MBS and
FBS is not considered.

In order to reduce the interference between macrocell and
femtocell, and that among femtocells, a weighted graph is
proposed in this paper, in which the vertex of the graph is
MUE or FBS. Based on the graph the resource allocation
problem fundamentally differs from those traditional graph-
based schemes. In our proposed scheme a fixed number of sub-
bands are used and the hybrid clustering based on interference
graph (HCIG) algorithm is proposed. After HCIG not only one
sub-band is assigned to MUE and FBS, but also other available
sub-bands are assigned to FBS under the interference constraint
to improve the spectrum efficiency.

In what follow, the discussion of this study after the
introduction is backgrouck, observation and methodlogy,
HCIG method and then the results with discussion and lastly
the conclusion.

II. Background

Long Term Evolution (LTE) has many features considered
for future fourth generation (4G) systems [11], but the
performance of LTE does not meet IMT -Advanced
requirements introduced by the International
Telecommunications Union (ITU) [12] which leaded to a need
for other releases. The evolved versions (LTE Release 10 and
beyond), named LTE Advanced, satisfy the requirements
defined by IMT -Advanced. Since data traffic demand in
cellular networks is exponentially growing, further increasing
of the node density is required to enhance the system spectral
efficiency. However, site acquisition costs can get
prohibitively expensive particularly in a space limited dense in
urban areas [13]. Therefore, several technologies have been
suggested to improve the performance of LTE- A networks.
One of the advanced technologies is to deploy heterogeneous
networks (HetNets).

A Heterogeneous Network consists of macrocells and low
power nodes including picocells and femtocells. They are
categorized in terms of transmit powers, antenna heights, the
access types, and the backhaul connection to other cells. The
goal of using low power nodes is to offload traffic from
macrocells, improve indoor coverage, and increase the spectral
efficiency through spectrum reuse. By this means, the larger
numbers of cells have access to more efficient spectrum reuse
and higher data rates [14].

III. Observations and Methodology

1. 1MB S, FUE is the Co-Channel Interference (CCI) caused by
MBS to FUE, e.g. the interference from MBS to FUE3.2)
IFBS,FUE is the CCI between femtocells, the interference
from femtocell2 to FUE1.3) IFBS,MUE is the CCI caused by
FBS to MUE, e.g. the interference from femtocelll to MUE1.

Fig. 1 Downlink Interference scenarios in LTE-Heterogeneous
Network

In order to terminate all the three types of interference shown
in Fig.l, an active interference graph construction scheme in
which the vertex of graph is a femto base station FBS and the
MUE which is suffering interference from FBS. As the

location of FBS is fixed and only partial MUEs are considered
in the graph, the overhead of updating the graph is low.
Our current problem is how to determine whether two nodes
can be connected by an edge in the graph and how to estimate
the interference influence. Note that the effect of interference
depends on the ratio of interference power to signal power, so
the Regional Average Channel State (RACS) metric is
proposed to evaluate the influence of interference. The RACS

of region m which is served by BS t and interfered by BS ■
represents the average SINR, and can be calculated as:
RACS (i, j,A m ) = jj SINR, j (x, y)dxdy I S{AJ (1)

An

Where SINR 1J (X,Y) = P ri (x,y)/p rJ (x,y) + N 0 ) ;
Pri(Prj)> * s me rece i ye d power from BS i (BS J ) ; A^ 0 is
the noise power; S(A m ) is the area of region m. Let Abe the
coverage region of BS ( and when
RACSiUj.A^KSINR^ orthogonal sub-bands should be
assigned to BS t and BSj to avoid interference. For the three

Scenarios shown in Fig.l, the interference threshold based on
RACS is given in the following argument.

A. A Interfernce between FBS's

We consider the situation in which FBS k and FBS . are
located at (0, 0) and (d,0), with circular coverage radius R k
and . When a FUE is located at (x, y) the received power
from FBS k and FBS • are as follows.

p r , k =p k d- k a =p k (x 2 +y 2 r n ( 2)

Pr^Pj^^P^x-df + yY 12 (3)
Where a is the path loss exponent, P k (P.) is the
transmit power of FBS k (FBSj) ; d k (dj) is the
distance from the FUE to FBS k (FBSj) . Let a = 2

and ignore the noise power, the SINR of the FUE
which is served by FBS k is:

SINR kj (xj)--

p rj +N0 p. x 2 + y 2

(4)

As the FUE is moving in the coverage area of
FBS k which is, the RACS of the coverage region of

FBS k is calculated as follows.

RACS(k,j,A k )= \ \siNR kj rdrdO/S(A k ) = ^(l+ ? d 2 In A.)

International Journal of Engineering Works

Vol. 1,PP. 10-14, Sept. 2014

Where R^is the minimum distance between FUE
and FBS.

When the power of FBS is fixed, the value of
RACS(k,j,A k ) is only related to the distance
between two FBSs. therefore, the SINR condition
RACS(k, j, A k ) < c th can be rewritten as the distance
function:

d<d^=M-Rl)(^-l)l(2\n^) (6)

A

^min

B. Interfernce from MBS toFBS

Consider the same situation complete in subsection
A, when there is a MBS M located at (D, 0) with

transmit power P M , the FUE served by FBS k will
suffer interference from the MBS. Similar to the
analysis in subsection A, the RACS of FBS k
caused by the interference from the MBS is:

P 2D 2 R
RACS(kM,A k ) = ^(l + - — In—

r M IX k A min A min

(7)

When RACS(k,M,\)<c th RACS(k,M ,A k ) <c th
we can get:

D D mn =J(Rl -R n )(^_ 1)/(21n ' _) (8)

A

1 k Rimn

To make simpler the expression, the FBS is called
inner FBS when the location of FBS satisfies
inequality.

C. Interfernce from FBS to MUE

In this situation that a MBS located at (0, 0) with
transmit power PM and FBS k located at (x f , y f )

with transmit power PF. When the MUE i served by
the MBS is located at (x, y), the SINR of the UE is:

SINR i (x,y) = -

Pf

(x-x f y+(y-y f y

2 2

x +y

(9)

P, F +N0

Where noise power is ignored; a is the path loss
exponent. In organize to estimate the interference
from FBS to MUE, the MUE interference region of
FBS is calculated, in which the SINR of the UE is
below a predefined threshold.

IV. HCIG CONSTRUCTION METHOD

In our proposed hybrid clustering interference graph (HCIG)
scheme, the interference graph G(V , E) is constructed by

MBS, where the vertex set V stands for all FBSs and the
MUEs which are in the interference region of FBS, and W is
the influence matrix to characterize the prospective
interference between two vertexes in which (/, j) = w(j,i) .

When w(i, j) = 0 , node/ and node/ is not connected in the
graph.

To judge whether two nodes are connected by an edge, the
distance threshold in subsection A and B as well as the
interference region in subsection C are utilized, in the
meantime, as MBS is not the graph vertex, inner FBS node
and MUE node are connected in the graph to avoid the
interference. As two MUEs can't be assigned the same
resources in LTE network, we let the weight between them be
wO which is a very large value. As MUE has higher priority

than FUE, W 0 is assigned to denote the interference from FBS

to MUE in order to guarantee the performance of MUE. For
other types of interference, 1/RACS is used to express the sum
of interference.

A. Resource Allocation in HCIG

HCIG is proposed to reduce the system interference and
improve the spectral efficiency, which is shown as follows.
Step 1 : one sub-band is randomly allocated to a cluster and the
nodes in the cluster reuse the same resource.
Step 2: In HCIG, orthogonal resources are allocated to MUE
and inner FBS in order to cancel the high interference from
MBS. Though, when there are not enough orthogonal
resources after the resource allocation of MUE in the graph
and inner FBS, the remaining MUE should reuse the sub band
which is used by inner FBS. To minimize the system
interference, the sub-band used by the inner FBS which is
farthest from the MBS is reused by the remaining MUE.

Step 3: After that, each FBS is assigned a sub-band. In order
to get better the spectrum efficiency of FBS, this step will
search more sub-bands which can be assigned to FBS on the
condition that the sub-bands are not used by the interfering
nodes. Through the graph connection information, a FBS
could know the resource set used by connected FBSs in the
graph. Therefore, the sub-bands which are unused by neighbor
FBSs are assigned to the FBS to improve the spectrum
efficiency.

V. Results and classification

The system simulation parameters are configured according to
3 GPP LTE condition [10], as presented in Table where Inter-
Station Distance (ISD) indicates the distance between two
neighbor MeNBs. In our simulation, 19 microcells are
considered, in each of which the same number of femto cells
are placed. Due to the interference from neighbor cells can't
be ignored, only the results of central 7 cells are collected. The

International Journal of Engineering Works

Vol. 1,PP. 10-14, Sept. 2014

MUEs are uniformly distributed over the macrocell area and
the FUEs are distributed in the coverage area of femtocells.
The SINR threshold for construction the interference graph is
set to 10 dB.

TABLE 1

Modal Parameters

Parameters

Femtocell

Microcell

System Bandwidth

20MHz

20MHz

Cell Layout

Circular Cell

Hexagonal Network

Cell Cize

Radius=18m

ISD=400m

Transmit Power

18dbm

41 dBm

Antenna Gain

OdBi

14dBi

Path Loss

126+30*logl0(d)

126+36.5*logl0(d)

Fast Fading

SCME

SCME

Daviation

4dB

4Db

Noise Level

-176dBm/Hz

-176dBm/Hz

UE Allotment

2 per cell

60 per cell

A. MUE and FUE SINR Results

The Cumulative Distribution Function (CDF) of femto user
equipment FUEs' SINR of all edge users. As the interference
from FBS to MUE is dynamically canceled by HCIG
proposed scheme remarkably improves the SINR performance
of FUE, especially reduces the number of FUEs with low
SINR. In addition, as only the interference among FBSs is
considered in adaptive frequency reuse (AFR), the FUEs'
SINR in AFR is similar to that in SFA as shows in Fig. 2.
The Cumulative Distribution Function (CDF) of Micro user
equipment MUEs' SINR of all edge users. As the interference
from MBS to FUE is dynamically canceled by HCIG, the
proposed scheme remarkably improves the SINR performance
of FUE, especially reduces the number of MUEs with low
SINR. In addition, as only the interference among MBSs is
considered in AFR, the MUEs' SINR in AFR is similar to that
in SFA as shows in Fig. 3.

The Cumulative Distribution Function (CDF) of inner MUEs'
SINR. The interference to MUE can be divided into two types:
from neighbor FBSs; from the MBS. In addition, the
interference from MBS to FUE is getting more seriously when
FUE is closer to the MBS. In AFR, only the interference from
neighbor FBSs is canceled; while in HCIG, the interference
from MBS is also canceled by assigning orthogonal resources
to MUEs and inner FBSs. So for inner FUEs, the SINR
performance insignificantly improved by HCIG compared to
SFA and AFFR; for outer FUEs, the SINR of FUEs is
improved similarly by AFR as shows innFig.4.
The Cumulative Distribution Function (CDF) of inner FUEs'
SINR. The interference to FUE can be divided into two types:
from neighbor MBSs. In addition, the interference from FBS
to MUE is getting more seriously when MUE is closer to the
FBS. In AFR, only the interference from neighbor MBSs is
canceled; while in HCIG, the interference from MBS is also
canceled by assigning orthogonal resources to MUEs and

inner FBSs. So for inner FUEs, the SINR performance
insignificantly improved by HCIG compared to SFA and
AFFR; for outer FUEs, the SINR of FUEs is improved
similarly by AFR as shows in Fig. 5.

1.5

0.5

Q

O

0.5-

- HCIG-AFR

20 40 60 80

SINR of All Edge-FU (dB)

100

Fig.2 All edge FU SINR CDF

5 10 15 20

SINR of All Edge-MU (dB)

25

Fig.3 All edge MU SINR CDF

•HCIG-AFR

10 20 30 40
SINR of All Center-MU (dB)

50

Fig.4 All Center MU SINR CDF

-•—HCIG-AFR

j i i i i i_

10 20 30 40 50 60 70 80 90
SINR of All Center-FU (dB)

Fig.5 All Center FU SINR CDF

International Journal of Engineering Works

Vol. 1,PP. 10-14, Sept. 2014

VI. CONCLUSION

Our proposed hybrid clustering interference graph (HCIG) in
which three types of interference is reduced. Also the best
clustering algorithm is formulated. After HCIG, not only the
minimum sub-bands are allocated to FBS, but also other sub
bands which are not interring with neighbor FBSs are assigned
to FBS to enhance the spectral efficiency. Furthermore, as the
location of FBS is fixed and only interfered MUEs are taken
as graph node, the overhead of updating the interference
graphing HCIG is very low. The system level simulation
shows that both the SINR of MUE and FUE are significantly
improved by HCIG.

Acknowledgment

Authors would like express great thanks for helpful
suggestions of Mr. Naveed Ur Rehman and Support from the
College of Information and Communication Engineering.

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International Journal of Engineering Works

Vol. 1,PP. 10-14, Sept. 2014